1. Field of the Invention
The present invention relates to an image processing device, an image processing method, and a computer-readable recording device for processing in-vivo images captured inside a body of a subject.
2. Description of the Related Art
Conventionally, endoscopes are widely used as a medical observation device that is introduced into the body of a subject, such as a patient, to observe the inside of a lumen. In recent years, swallowable endoscopes (capsule endoscopes) have been developed that are provided with an imaging device, a communication device, and the like in a capsule-shaped casing and that wirelessly transmit image data captured by the imaging device to the outside of the body. The number of in-vivo images (intra-gastrointestinal images) sequentially captured by such a medical observation device is huge (more than several tens of thousands), and considerable experience is required to make observation and diagnosis of each intra-gastrointestinal image. Therefore, there is a demand for a medical diagnosis support function for supporting doctors in the diagnosis. As one of image recognition techniques that realize such a function, a technique has been proposed in which an abnormal area, such as a lesion, is automatically detected from an intra-gastrointestinal image and an image that needs to be focused on in the diagnosis is presented.
Meanwhile, intra-gastrointestinal images sometimes contain contents, such as residue, that need not be observed, in addition to a mucosal area to be observed in the diagnosis. As a technique for distinguishing between the mucosal area and the contents area (i.e., categories of areas), for example, Japanese Laid-open Patent Publication No. 2010-115413 discloses an image processing method, in which a plurality of images are selected from a series of intra-gastrointestinal images, color feature data is calculated for each pixel or for each small area of the selected images, and a mucosal area in each of the images constituting the series of the intra-gastrointestinal images is identified on the basis of the color feature data.
Furthermore, as a technique for distinguishing between different areas that appear in an image, a method based on texture feature data using a co-occurrence matrix is known (see, for example, Okutomi Masatoshi et al., “Digital Image Processing”, CG-ARTS Society, pp. 194 to 195). The co-occurrence matrix is a matrix whose elements are the probabilities Pδ (Li, Lj) that pairs of pixel values (Li, Lj) occur on the assumption that Li and Lj represent respective pixel values of a pixel i and a pixel j that is deviated from the pixel i by predetermined displacement δ (d, θ) (d is a distance and θ is an angle). With use of such a matrix, it is possible to obtain the feature data indicating the properties, such as homogeneity, directionality, or contrast, of the pixel values.